Boosted of Haar-like Features and Local Binary Pattern Based Face Detection

Effective and real time face detection has been made possible by using the method of rectangle Haar-like features with AdaBoost learning and cascade of the strong classifiers since Viola and Jones´ work. After that, Rainer Lienhart had improved Viola and Jones´ work by extending set of Haar-like features. However, it still has drawbacks; the detection results often have high false positives. In A. Hadid et al. have used local binary pattern (LBP) method for face description and they applied effectively in face detection problem. However, it is slow. Therefore, it is difficult to apply in real time applications. In this work, we proposed an approach to combine a boosted of Haar-like features and LBP to achieve a good trade-off between two extreme. The system, which is built from proposed model, is conducted on MIT + CMU test set. Experimental results show that our method performs favorably compared to state of the art methods.